Safety Evaluation of Green Light Optimal Speed Advisory (GLOSA) System in Real-World Signalized Intersection

Author:

Suzuki Hironori,Marumo Yoshitaka, ,

Abstract

The use of green light optimal speed advisory (GLOSA) systems is seen as a key application for achieving more environmentally friendly, time-efficient, and safer traffic flows at signalized intersections. In previous papers, the authors have proposed a GLOSA system that informs drivers of the most appropriate position for their vehicle instead of their optimal speed. This paper reports on a performance evaluation of our proposed GLOSA system after application to morning rush-hour traffic flow in a simulation of a real-world signalized intersection. A performance evaluation of this numerical simulation showed that our GLOSA system increased the time headway of vehicles and decreased their deceleration rates in the vicinity of the signalized intersection. In addition, the use of the system moderately increased fuel efficiency without affecting vehicle travel time. From these results, it can be concluded that our proposed GLOSA system has the potential to create safer traffic flows in real-world signalized intersections without degrading traffic efficiency.

Publisher

Fuji Technology Press Ltd.

Subject

Electrical and Electronic Engineering,General Computer Science

Reference27 articles.

Cited by 8 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Examining road safety impacts of Green Light Optimal Speed Advisory (GLOSA) system;Accident Analysis & Prevention;2024-06

2. GeoAI-Powered Lane Matching for Bike Routes in GLOSA Apps;Proceedings of the 31st ACM International Conference on Advances in Geographic Information Systems;2023-11-13

3. Mixed-traffic Intersection Management using Traffic-load-responsive Reservation and V2X -enabled Speed Coordination;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

4. Accurate Bike Routing for Lane Prediction in GLOSA Apps via Infrastructure Reference Models;2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC);2023-09-24

5. Turning at Intersections Using Virtual LiDAR Signals Obtained from a Segmentation Result;Journal of Robotics and Mechatronics;2023-04-20

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